code: def test_raw_padder():
      backend = "raw"
      batch_field = [1, 2, 3]
      padder = get_padder(
          batch_field,
          pad_val=0,
          backend=backend,
          dtype=int,
          field_name="test",
      )
      pad_batch = padder(batch_field)
      assert pad_batch == batch_field
  
      batch_field = [[1], [2, 2], [3, 3, 3]]
      padder = get_padder(
          batch_field,
          pad_val=0,
          backend=backend,
          dtype=int,
          field_name="test",
      )
      pad_batch = padder(batch_field)
      assert np.shape(pad_batch) == (3, 3)
  
      batch_field = [[[1]], [[2, 2], [2]], [[3], [3], [3]]]
      padder = get_padder(
          batch_field,
          pad_val=0,
          backend=backend,
          dtype=int,
          field_name="test",
      )
      pad_batch = padder(batch_field)
      assert np.shape(pad_batch) == (3, 3, 2)
  
      batch_field = [np.ones((3, 3)), np.ones((2, 3)), np.ones((1, 0))]
      padder = get_padder(
          batch_field,
          pad_val=0,
          backend=backend,
          dtype=int,
          field_name="test",
      )
      pad_batch = padder(batch_field)
      assert isinstance(pad_batch, list)
      assert np.shape(pad_batch) == (3, 3, 3)
      assert (pad_batch == np.zeros(np.shape(pad_batch))).sum() == 12
  
file_path: fastNLP/tests/core/collators/padders/test_get_padder.py
imports: import pytest
  import numpy
  from fastNLP.core.collators.padders.get_padder import get_padder, InconsistencyError, DtypeError, _get_element_shape_dtype
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH, _NEED_IMPORT_PADDLE, _NEED_IMPORT_JITTOR, _NEED_IMPORT_ONEFLOW
label_desc: Use image node_id 3 for calling a global function with example usage: test_raw_padder() without return types